Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼ 150 – 350 MeV . We use ...Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma's final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
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CMK, CTK, FMFMET, IJS, NUK, PNG, UL, UM
A new method for quantifying fluctuations in the initial state of heavy ion collisions is presented. The initial state energy distribution is decomposed with a set of orthogonal basis functions which ...include both angular and radial variation. The resulting two-dimensional Fourier coefficients provide additional information about the nature of the initial state fluctuations compared to a purely angular decomposition. We apply this method to ensembles of initial states generated by both Glauber and color glass condensate Monte-Carlo codes. In addition initial state configurations with varying amounts of fluctuations generated by a dynamic transport approach are analyzed to test the sensitivity of the procedure. The results allow for a full characterization of the initial state structures that is useful to discriminate the different initial state models currently in use. Communicated by Steffen Bass
A major challenge in plant ecology is quantifying how roots obtain water and nutrients from the soil. Stable-isotope analysis of hydrogen and oxygen in plant and soil water is one of the best and ...least destructive methods for elucidating plant-soil interactions. Plant roots obtain water from various depths in the soil and the isotopic signature of plant stem water reflects the soil water sources. Current methods for inferring plant water sources based on stable isotopes ("simple linear mixing models") are limited. First, their formulation restricts the number of water sources to a maximum of three (e.g., surface, intermediate, deep-soil water); estimation of additional sources leads to an identifiability problem. Second, simple linear mixing models do not appropriately reflect uncertainty, and most importantly, they cannot be employed to elucidate behavior of the root system itself, such as root activity for water uptake. This study introduces the RAPID (root area profile and isotope deconvolution) algorithm, a powerful approach for reconstructing plant water uptake and root area profiles. The RAPID algorithm overcomes the nonidentifiability problem by incorporating a biophysical model for root water uptake into a Bayesian framework such that the biophysics and prior distributions place biologically realistic constraints on the profiles. Posterior distributions for the proportions of active root area and water acquired from each soil layer are obtained via Markov chain Monte Carlo. We apply the RAPID algorithm to data collected for a desert shrub and examine its sampling implications.
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BFBNIB, FZAB, GIS, IJS, INZLJ, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
Doubly stochastic Bayesian hierarchical models are introduced to account for uncertainty and spatial variation in the underlying intensity measure for point process models. Inhomogeneous gamma ...process random fields and, more generally, Markov random fields with infinitely divisible distributions are used to construct positively autocorrelated intensity measures for spatial Poisson point processes; these in turn are used to model the number and location of individual events. A data augmentation scheme and Markov chain Monte Carlo numerical methods are employed to generate samples from Bayesian posterior and predictive distributions. The methods are developed in both continuous and discrete settings, and are applied to a problem in forest ecology.
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BFBNIB, INZLJ, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK, ZRSKP
Most probable number (MPN) and colony-forming-unit (CFU) estimates of fecal coliform bacteria concentration are common measures of water quality in coastal shellfish harvesting and recreational ...waters. Estimating procedures for MPN and CFU have intrinsic variability and are subject to additional uncertainty arising from minor variations in experimental protocol. It has been observed empirically that the standard multiple-tube fermentation (MTF) decimal dilution analysis MPN procedure is more variable than the membrane filtration CFU procedure, and that MTF-derived MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the variability in, and discrepancy between, MPN and CFU measurements. We then compare our model to water quality samples analyzed using both MPN and CFU procedures, and find that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our results indicate that MPN and CFU intra-sample variability does not stem from human error or laboratory procedure variability, but is instead a simple consequence of the probabilistic basis for calculating the MPN. These results demonstrate how probabilistic models can be used to compare samples from different analytical procedures, and to determine whether transitions from one procedure to another are likely to cause a change in quality-based management decisions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Rapid tastant detection is necessary to prevent the ingestion of potentially poisonous compounds. Behavioral studies have shown that rats can identify tastants in approximately 200 ms, although the ...electrophysiological correlates for fast tastant detection have not been identified. For this reason, we investigated whether neurons in the primary gustatory cortex (GC), a cortical area necessary for tastant identification and discrimination, contain sufficient information in a single lick cycle, or approximately 150 ms, to distinguish between tastants at different concentrations. This was achieved by recording neural activity in GC while rats licked four times without a liquid reward, and then, on the fifth lick, received a tastant (FR5 schedule). We found that 34% (61 of 178) of GC units were chemosensitive. The remaining neurons were activated during some phase of the licking cycle, discriminated between reinforced and unreinforced licks, or processed task-related information. Chemosensory neurons exhibited a latency of 70-120 ms depending on concentration, and a temporally precise phasic response that returned to baseline in tens of milliseconds. Tastant-responsive neurons were broadly tuned and responded to increasing tastant concentrations by either increasing or decreasing their firing rates. In addition, some responses were only evoked at intermediate tastant concentrations. In summary, these results suggest that the gustatory cortex is capable of processing multimodal information on a rapid timescale and provide the physiological basis by which animals may discriminate between tastants during a single lick cycle.
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